Laser processing of materials such as laser welding, laser annealing, laser cutting and laser cladding of metals and non-metals alike has become an invaluable tool in many industries. For example, laser welding of metal, in any joint configuration, involves the use of laser radiation to heat the surface to temperatures at which melting and, in the case of penetration or "keyhole" welding, some material vaporization occurs. The size of the localized area on the surface, or joint, where this process takes place can be adjusted by an external means, usually by a focusing lens or mirror to adjust the focal point of the laser beam. However, the quality of the weld (weld penetration, morphology, porosity and metallurgical characteristics) can be affected by a number of factors, some of which may rapidly fluctuate during the welding process. The principal variables which can be used to characterize a laser process are divided into three categories; 1) laser beam characteristics such as laser power, beam mode, the temporal profile etc.; 2) laser beam delivery characteristics such as process speed, focal position and the like; and 3) physical and chemical properties of the workpiece such as reflectivity which have an impact on the laser-material interaction, and surface contamination.
The phrase "laser processing" as used herein refers to processes such as laser welding, cladding etc., and the phrase "process speed" as used herein means the rate (distance per unit time or area per unit time) at which the process occurs. This process speed is related to the rate at which a sufficient amount of energy from the laser beam is converted to heat in the workpiece (energy per unit length). The processing may be achieved either by scanning the workpiece under a fixed laser beam or vice versa or by changing laser pulse repetition rate, duty cycle and the temporal pulse profile. When the process is laser welding the process speed is the welding speed.
To illustrate, in CO.sub.2 laser penetration welding in sheet steel, the quality of the weld is dramatically reduced when either too little or too much penetration occurs. This occurs when the energy deposition rate is either too high or low and may be corrected by adjusting either the welding speed or laser power. Further, in the case of processing highly reflective metals such as aluminum, the ability to sustain a weld pool is problematic because of the uncertainty of the laser beam coupling to the workpiece. Rapid changes in coupling between the laser beam and workpiece can occur and to maintain a stable welding process corresponding adjustments in laser power, welding speed or focal position are required.
Work on sensor development for in-process integration and optimization of high speed CO.sub.2 laser interactions such as laser welding has been underway for a number of years. Chen, H. B., Li, L., Brookfield, D. J., Williams, K. and Steen, W. M., Laser Process Monitoring with Dual Wavelength Optical Sensors, ICALEO'91 proceedings, L.I.A. Vol. 74, ICALEO (1991), pp. 113-122, discloses how radiation emitted from the laser-material interaction zone can be analyzed using photodiodes sensitive in infrared (1-2 .mu.m) and ultraviolet (300-500 nm) bands. Comparison of signals from both bands provide information on the quality of the laser weld or cut.
The reference Denney, P. E., Metzbower, E. A., Synchronized Laser-Video Camera System Study Of High Power Laser Material Interactions., ICALEO '91 proceedings, L.I.A. Vol. 74, ICALEO (1991), pp. 84-93 discloses how a strobed laser-camera system may be used to study the laser beam-material interaction zone. The vision system was a pulsed N.sub.2 (nitrogen) laser (337 nm) that is synchronized with a CCD (charge coupled device) video camera. The studies resulted in a series of video tape recordings in which laser welds and laser cladding processes were studied.
Farson, D. F., Fang, K. S., Kern, J., Intelligent Laser Welding Control, ICALEO'91 proceedings, L.I.A. Vol. 74, ICALEO (1991), pp. 104-112 discloses how an artificial neural network can be used to analyze acoustic emissions from a weld pool for determination of weld penetration. The output signals from a microphone were digitized and fast fourier transformed with the resulting power spectrum divided into 16 bands which, when averaged, were input into the neural network. Resulting predictions of penetration were obtained at the relatively slow rate of 3 Hz. Attempts at closed loop control using this technique were inconclusive.
Closed loop auto-focusing systems are now almost standard equipment for many laser cutting applications. The distance from the cutting nozzle to the workpiece is preset, and during the cutting process, this distance is maintained within a small margin of error. Similarly, laser power may be controlled by sampling a known fraction of the output beam through a leak mirror in the laser cavity arid adjusting the current in the laser discharge accordingly to stabilize the output power. A drawback to both these methods of control is that they do not use information from the laser-material interaction zone directly.
Sensors suitable for monitoring the laser-material interaction zone directly may be roughly divided into two categories. In the first, sensors such as microphones for measuring sound and photo-diodes for detection of light intensity return information relating to the strength or intensity of the signal generated from the laser-material interaction zone. The second category of sensor provides spatial information of this zone. For example, a charge coupled device (CCD) camera is capable of providing spatial information, that is, how the light generated from the process is distributed throughout the video frame.
However, to date the use of machine vision in which video images have been used to acquire spatial information of the laser-material interaction zone has been limited to diagnostic applications only as disclosed in Denney et al. light from a second laser source irradiates the laser-material interaction zone or weld pool at a specific wavelength where plasma light emission is weak and the reflected light from the weld pool is viewed by the CCD camera through a narrow bandpass filter. This technique is successful as a diagnostic toot but it is expensive and to date no real-time feedback control of primary processing variables has been attempted due primarily to the prohibitive time constraints involved in acquiring and transferring digital images from the frame grabber to the host computer for analysis.
Therefore it would be advantageous to provide a real-time control system for laser processing which utilizes feedback from the laser-material interaction zone using sensors from either of the afore-mentioned categories to control the laser process speed which avoids the prior art time constraints for acquiring and manipulating the sensor data.